We take security seriously and actively maintain security updates for the following versions:

If you discover a security vulnerability, please report it to us as follows:

• Email: security@pytorch-distributed-training.dev
• Response Time: Within 48 hours
• Updates: Regular updates on investigation progress

Please include the following information in your report:

• A clear description of the vulnerability
• Steps to reproduce the issue
• Potential impact and severity assessment
• Any suggested fixes or mitigations
• Your contact information for follow-up

• Do not create public GitHub issues for security vulnerabilities
• Do not disclose the vulnerability publicly until we've had a chance to address it
• Do not attempt to exploit the vulnerability beyond what's necessary to demonstrate it

• Keep dependencies updated
• Use secure coding practices
• Validate all inputs and outputs
• Implement proper error handling
• Follow the principle of least privilege
• Use secure random number generation
• Implement proper authentication and authorization

• Keep the framework and dependencies updated
• Use secure network configurations
• Implement proper access controls
• Monitor for suspicious activity
• Use secure credential management
• Regular security audits and penetration testing

• Input validation and sanitization
• Secure random number generation
• Proper error handling without information leakage
• Secure default configurations
• Dependency vulnerability scanning
• Automated security testing

• Bandit: Static security analysis for Python
• Safety: Dependency vulnerability checking
• CodeQL: Automated security analysis
• Dependabot: Automated dependency updates

1. Triage: Initial assessment and prioritization
2. Investigation: Detailed analysis of the vulnerability
3. Fix Development: Create and test security fixes
4. Deployment: Roll out fixes with minimal disruption
5. Communication: Notify affected users appropriately
6. Post-mortem: Analyze and improve response process

• Security advisories will be published on GitHub
• Critical fixes will be deployed as hot patches
• Users will be notified through multiple channels
• Clear upgrade instructions will be provided

• Security patches are prioritized and fast-tracked
• Patch versions are released within 7 days of fix availability
• Critical security fixes may result in immediate releases
• Backporting to supported versions as appropriate

• Security fixes maintain backward compatibility when possible
• Breaking changes are clearly documented
• Migration guides provided for necessary changes

Security researchers who responsibly disclose vulnerabilities will be:

• Publicly acknowledged (with permission)
• Added to our security acknowledgments
• Considered for bounties (when available)
• Invited to join our security advisory group

• Security Issues: security@pytorch-distributed-training.dev
• General Security Questions: security@pytorch-distributed-training.dev
• PGP Key: Available upon request
• Response SLA: 48 hours for initial response, 7 days for updates

This security policy applies to the PyTorch Distributed Training Framework core project. Third-party integrations, plugins, and user code are the responsibility of their respective maintainers.